Boost campaign performance with Adobe Content Analytics.
The challenge
Creative asset and marketing campaign performance frequently remain in data silos, with reports coming from different vendors and systems. It’s difficult to stitch together the data to gauge the impact of content. So now’s the time to take it one step further, to enable brands to understand how all their assets impact performance across channels — with the help of AI.
According to eMarketer, brands are still cautiously optimistic about AI’s ability to drive growth. However, 74% are already using AI to accomplish tasks such as content analysis, development and ideation, programmatic advertising and media buying, predictive analytics for customer insights, and research to identify trends. AI’s use in personalization and customer experience is a priority for 58% of marketers, highlighting the importance marketers place on tailoring content and interactions to individual consumer preferences.
3 in 4 marketers are using AI for content creation — with most “cautiously optimistic” about its ability to drive growth.
Marketers are still grasping for better ways to measure and analyze content impact. A/B testing can offer some insights, but it is nearly impossible to understand the specific attributes of an image or experience that resonate, and for which customers and in which channel. Moreover, complex workflows, varying content types, and data silos present a challenging picture.
Typical content workflow between creators, analysts, and marketers.
What is Content Analytics?
AI and machine learning services break down every experience built with your DAM (digital asset management system) across paid and owned channels, into their content elements and descriptive attributes, creating a complete metadata profile of assets and experiences. Marketers are then able to correlate customer interactions with the aspects of those assets and experiences that deliver positive outcomes. Then, by understanding customers’ affinities, organizations are better able to personalize content at scale.
Marketers and analysts can analyze content in their Content Analytics instance to have a full view of the entire customer journey, across all touchpoints.
How Content Analytics will help businesses
Content Analytics surfaces important content insights on the many assets that various teams apply within their products, services, apps, and marketing campaigns daily. The benefits of having this information include:
- Better ability to personalize content. Increase engagement and conversions using content analysis and engagement.
- Improved understanding of marketing spend. See activity by marketing channel, take it one step further with asset details, understand what asset is attributed to marketing channel success, and extend that to other channels or campaigns to eliminate wasted ad and marketing spend.
- More effective reengagement. Drive forward with digital strategy for converting researchers to buyers by leveraging content level performance on top of page interactions and events to establish ROI of campaigns, marketing channels, and materials.
- Audience growth. Test out content on digital channels and tie creative back to marketing budget allocation to see which campaigns were the most effective in growing audiences and customer LTV.
- Increase revenue. Analyze the site’s product performance by identifying the highest converting items and determining the last viewed image that led to each conversion. Investigate whether these conversions contributed to additional purchases or repeat transactions, thereby attributing them to the overall revenue earned.
The types of business questions you can address
To get started with Content Analytics, it’s important to consider what types of questions you want to address with the information collected. From there, you can develop a content strategy for your assets aligned to business goals and continually compare performance. This content analysis reporting can then be shared to various stakeholders. You can start with questions like:
- How often are assets being used?
- Has their performance improved, declined, or remained stagnant?
- Where is the asset performing best — for example, in a particular section, page, or placement?
- How much is the asset contributing to revenue on my site?
- How long are users engaging with my site once they have been exposed to the asset?
- How often do they come back after being exposed to the asset?
- Is there a specific trait that resonates the best or worst across my assets?
- Which asset or trait has performed strongest and was the most effective in past similar campaigns?
- Which marketing channel is my asset or trait performing the best against engagement and visitation?
Use cases
EMarketer states over half of marketers (55%) use AI for content ideation, indicating the technology’s value in generating new concepts and strategies. Here are some industry use cases that can be applied with Content Analytics to help with content ideation, analysis, and optimization.
Travel and hospitality
Off-season sales are lacking for many hotel brands. Use behavioral and user insights to optimize campaigns by seeing which creative assets for hotels or locations and which elements (for example, mountains, green spaces, or cities) are ending in bookings. Then present these assets to similar groups of users, thereby driving revenue.
Media and entertainment
Before a new show premieres, determine which creative asset or ad leads to show page visits, searches, or watches to determine the best performing asset and capitalize on post-premiere opportunities to engage non-watchers.
Finance
New home buyers are shopping for good mortgage rates. Gain clarity on which creative asset or ad is eventually resulting in loan applications to optimize campaigns with the creative elements (for example, a young couple, singles, or the type of home) that lead to successful conversions.
Retail and CPG
During back-to-school season, identify the asset and design elements in your paid campaigns that are driving customer clicks and conversions on your website to understand trends. Then promote those assets across your marketing channels, targeting users whose profiles are similar to those of the conversion group.
Adobe Content Analytics can further help brands identify key trends and attributes in their creative assets that lead to real business impact and influence the customer journey.
You can find more information about Adobe Content Analytics here. Discover how we enable omnichannel content analysis and audience segmentation, now with asset-level data and performance.
FAQs
There are two types of content analysis — conceptual analysis, which analyzes how frequently the same concepts appear in content, and relational analysis, which analyzes how different content concepts are related to one another.
Cataloging content helps you to efficiently organize, discover, and access information when analyzing content.
Cataloging content allows for easy discovery, improvement content management, enhanced collaboration between product teams, and real-time data reporting for all internal teams.
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